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A threaded Web graph (Power law random graph) generator written in Python. It can generate a synthetic Web graph of about one million nodes in a few minutes on a desktop machine. It implements a threaded variant of the RMAT algorithm.
A simple statemachine library in java. It uses the memento pattern so the state is stored outside the machine so it is easier to cluster a solution using this statemachine.
Animants are virtual ants. Their name comes from the combination of "ants" and "animats", an animat being "a sofware approximation of a living creature".
Animants aim to simulate the behaviour of living animals.
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Hipo is a hypothetical computer to facilitate the learning of machine language. The student can use hipo to develop simple programs and understand the internal logic of a computer. There is a plan to implement Donald Knuth's MMIX machine language, also.
Machine learning toolkit for unsupervised and semi-supervised clustering that demonstrates excellent results on real-world data (see Bekkerman et al. ICML-2005 and ECML-2006).
Conrad is both a high performance Conditional Random Field engine which can be applied to a variety of machine learning problems and a specific set of models for gene prediction using semi-Markov CRFs.
jStates is a java library for easy state machine design and implementation.It uses XML to define states and state transitions. jStates is aimed at easy integration with desktop J2SE applications, Struts, Commons Validator, Web and other J2EE technologies
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K-automaton is a new parsing (syntactic analysis) machine isomorphous to language. Implemented in Java. Can generate Java code from grammars described in EBNF.
Refal.NET - Versatile, Compact yet Powfull Text Transformer and Compiler-Writing System. Based on Refal.NET VirtualMachine (+Refal.NET Compiler), this RAD-tool might be used for rapid prototyping, decreasing up to 10 times development efforts.
GLARE is a library and a software for product based optimization of reagent lists in the context of a chemical combinatorial library design. Large virtual combinatorial libraries containing 10^12 products have been optimized within a second.
KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.
MultiBoost is a C++ implementation of the multi-class AdaBoost algorithm. AdaBoost is a powerful meta-learning algorithm commonly used in machine learning. The code is well documented and easy to extend, especially for adding new weak learners.
YABI93 is an Interpreter for the esoteric programming language Befunge, version "Befunge93". It is written in Java 1.5 and uses Swing for its graphical interface. YABI supports a multilanguage GUI.
The OS561 operating system based around FORTH/Java. The OS is to run on a VHDL chip OpenHardware design called the Minon, but could become available for other platforms. The unique point of the design is a revolutionary data compression technology.
This is a library for an extensible framework for range encoding. The framework is an extensible object-based state machine where probabilities are chosen based on the current frame the machine is in.
Takthons provides container and manipulation services for evolved machine language routines. This allows the calling application to concentrate on the UI, the fitness evaluation and the genetic operations rather than the machine language details.
A standalone, STL interface to the Torch library's Support Vector Machine (SVM). It supports single or multiclass (one vs. all) classification using dot product, polynomial, Gaussian and sigmoid kernels.
A Visual Studio .NET C++ application can perform machine learning using genetic algorithm, naive bayes, KNN, and Artificial Neural Networks (ANNs) read and processed from any standard ARFF.
Weka++ is a collection of machine learning and data mining algorithm implementations ported from Weka (http://www.cs.waikato.ac.nz/ml/weka/) from Java to C++, with enhancements for usability as embedded components.
A human-readable ISC-Licensed implementation of the LZO1X algorithm.
...The main problem with LZO is that it is absolutely not human readable.
People have done crazy stuff to get LZO to run in their language. Usually it implies inline assembly or trying to execute data which actually contains machine code. This is sick. Whoever is responsible for this sorry situation ought to be ashamed.
So I'm going to deobfuscate LZO and provide a ISC implementation of this algorithm in Python and C. In addition, I will provide a textual description of the algorithm so that it can be easily ported to any programming language.
I expect a severe performance degradation, but I leave optimizing for speed to other people.